Staff Engineer, Machine Learning Engineering (Heterogenous SW, Adreno GPU)

Qualcomm•San Diego, CA

62d

About The Position

Artificial Intelligence is changing the world for the benefit of human beings and societies. QUALCOMM, as the world's leading mobile computing platform provider, is committed to enable the wide deployment of intelligent solutions on all possible devices - like smart phones, laptops, autonomous vehicles, robotics and IOT devices. Qualcomm is creating building blocks for the intelligent edge. We are part of Qualcomm AI Research, and we focus on advancing Gen AI Technology for the Edge - including model fine tuning, hardware acceleration, model quantization, edge inference and related fields. Come join us on this exciting journey. In this particular role, you will work in a dynamic research environment, be part of a multi-disciplinary team of researchers and software engineers who work with cutting edge AI frameworks and tools. You will architect, design, develop, test, and deploy on- and off-device frameworks enabling optimization. The successful applicant should have a strong theoretical background and proven hands-on experience with enabling on-device AI using modern software engineering best practices.

Requirements

Strong theoretical background in AI and general ML techniques
Proven hands-on experience evaluating and optimizing Generative AI workflows for accuracy, performance, and other key metrics
ML Accelerator architecture knowledge & experience with ML Accelerators - GPU/NPU
Proven hands-on experience building LLM stacks to solve real-world problems
Strong Python and modern C++ design and implementation skills.
Strong command of Machine Learning training frameworks (i.e. PyTorch )
Proven hands-on experience establishing a high-quality software delivery process using industry best-practices (code review, CI/CD, automation, etc.)
Strong Linux command line skills.
Strong general analytical and debugging skills.
Prior experience working in agile environments.
Prior experience in collaborating with multi-disciplinary teams across time zones.
Strong team player, communicator, presenter, mentor, and teacher.
Bachelor's degree in Computer Science, Engineering, Information Systems, or related field and 2+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
Master's degree in Computer Science, Engineering, Information Systems, or related field and 1+ year of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
PhD in Computer Science, Engineering, Information Systems, or related field.

Nice To Haves

Hands-on experience developing software for heterogenous platforms with OpenCL.
Experience developing solutions that target a variety of hardware ( CPU, GPU, NSP …) along with their respective SW development environments.
Prior experience with model quantization, profiling and running models on edge devices.
Experience developing SDKs/libraries targeting multiple platforms and operating systems (Android, Linux, Windows)
Previous experience with Docker and Git.
Master's and/or PhD degree in Computer Science, Engineering, Information Systems, or related field and 5+ years of work experience in Software Engineering, Systems Engineering, or related.